Abstract: Research Problem: The need for greater flexibility, intelligence, and adaptability in robotic systems beyond traditional, pre-programmed automation. Objectives : To explore how AI, specifically machine learning and computer vision, enhances robotic capabilities, to evaluate the performance of an AI-driven system, and to discuss its implications. Methods: Briefly describe the research approach, such as a simulation-based experiment using reinforcement learning to train a robotic arm, a case study analysis of a specific industry, or a comprehensive literature review. Key Findings: State the primary results, for example, "The AI-driven system achieved a 25% increase in task completion speed and a 40% reduction in error rates compared to conventional automation. Conclusion: Summarize the overall significance of the findings for the field.

Downloads: | DOI: 10.17148/IJIREEICE.2025.13927